An Introduction to Oracle Enterprise Metadata Manager

The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098

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Data Discovery & Lineage in Enterprise Hadoop

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This document provides information about Aetna, a health insurance company. It summarizes that Aetna serves about 46 million customers to help them make healthcare decisions and manage healthcare spending. Aetna offers various medical, pharmacy, dental, life, and disability insurance plans as well as Medicaid services and behavioral health programs. As of March 2015, Aetna had approximately 23.7 million medical members, 15.5 million dental members, and 15.4 million pharmacy members. Aetna works with over 1.1 million healthcare professionals across more than 674,000 primary care doctors and specialists located in 5,589 hospitals across the US and globally.

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bidwhm

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My team embarked on building a data lake for our sales and marketing data to better understand customer journeys. This required building a hybrid data pipeline to connect our cloud CRM with the new Hadoop Data Lake. One challenge is that IT was not in a position to provide support until we proved value and marketing did not have the experience, so we embarked on the journey ourselves within the product marketing team for our line of business within Progress. The key to delivering on this was using standard interfaces using a bi-directional data pipeline to connect the systems. On the Salesforce side, we were able to get frictionless access to the data lake using clicks-not-code via OData. On the Hadoop side, we were able to ingest data from Salesforce using JDBC for Apache Sqoop. Join us to hear best practices and lessons learned.

Salesforce External Objects for Big Data

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30 for 30: Quick Start Your Pentaho Evaluation

Pentaho

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What Is Power BI? | Introduction To Microsoft Power BI | Power BI Training | ...

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The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is driving a market demand to expose more data from APIs. Business analysts, data engineers, and data scientists have been getting left behind in existing API strategies. This is because many APIs are designed to integrate with applications to extend functionality, however these data workers are looking for APIs that facilitate direct data access to support analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers in this $30 billion market.

Enterprise data science - What it takes to build?

Jothi Periasamy

Enterprise data science is not just creating dashboard, reports, ad-hoc query, models and/or algorithms, it’s beyond all - Take a look at our approach to enterprise data sciences, it’ very complex and it’s very difficult to implement as it’s involved integrating data across enterprise business function regardless of data source, format and structure There are many instances where people talk about enterprise data sciences (Oracle 12C, HADOOP, SAP) but “have you seen enterprise data sciences in a real system as a live demo”, in most cases the answers is “no” but now there is an opportunity to review enterprise data sciences with CloneSkills. I would say confidently say that there is no one in the world who integrated “Oracle 12C” and SAP HANA with HADOOP for real-time data integration except CloneSkills technical architect Mr. Karthik

Enterprise Information Management

Tomorrow’s industry leaders are the ones that draw new insights by creatively combining the data they have today. That can be a real challenge for most companies, especially since data types and volumes have grown astronomically over the last decade. And when you pair that with the tasks of gathering, organizing, and managing information from all over an organization and ensuring its accuracy, you have quite a job on your hands. But with our comprehensive portfolio of enterprise information management solutions, your business can unlock the power of its data, achieve entirely new insights, and use them to create a winning future.

Firewall friendly pipeline for secure data access

This webinar discusses how to establish secure connections between cloud applications and on-premises data behind firewalls. It presents common connection options like VPNs, SSH tunneling, and reverse proxies, and recommends a vendor-agnostic service that provides a managed open data connection. The webinar covers best practices for scalability, availability, and end-to-end monitoring. It provides examples of how BOARD and Intuit leverage such a connection service to access on-premises data from their cloud applications.

Contact Centers Powered by Esgyn

Rajender K Salgam

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Milomir Vojvodic

This document summarizes Oracle's data integration and governance solutions including Oracle GoldenGate, Oracle Data Integrator, Active Data Guard, Enterprise Data Quality, and Enterprise Metadata Manager. It discusses how these solutions provide real-time data replication, ETL, disaster recovery, data quality, and metadata management capabilities. The document also highlights new subscription-based offerings on the cloud for these solutions and how they can help reduce costs, improve data quality, and enable better data governance.

The Model Enterprise: A Blueprint for Enterprise Data Governance

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Data Governance Initiative

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The document discusses Apache Atlas, an open source project aimed at solving data governance challenges in Hadoop. It proposes Atlas to provide capabilities like data classification, metadata exchange, centralized auditing, search and lineage tracking, and security policies. The architecture would involve a type system to define metadata, a graph database to store metadata, and search and lineage functionality. A governance certification program is also proposed to ensure partner solutions integrate well with Atlas and Hadoop.

Operationalizing Data Analytics

VMware Tanzu

Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results. Learn about: Challenges Hadoop introduces, and how the right tools and platforms can help address them Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases Watch the on-demand webinar here: http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd

What is the Value of SAS Analytics?

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What are the the main areas of analytics and how can they benefit your business? Learn the value of SAS analytics and how you can get better insight into your data to make more profitable decisions. By getting a better understanding of your data you will know which part of the data can be reliably forecast using time series methods and which cannot. You will also gain an understanding of any hierarchical structure in the data that can be used.

Welcome to the Era of Open Analytics

Cloud applications are seeing a deluge of requests to support the exploding advanced analytics market. “Open analytics” is the emerging strategy to deliver that data through an open data access layer, in the cloud, to be directly consumed by external analytics tools and popular programming languages. An increasing number of data engineers and data scientists use a variety of platforms and advanced analytics languages such as SAS, R, Python and Java, as well as frameworks such as Hadoop and Spark. Cloud APIs are commonly designed to support application integration representing a disconnect with the analytics ecosystem. These combined trends create significant demand for a “bring-your-own-analytics” (BYOA) capability for cloud applications. Your cloud may already be smart, but giving users frictionless access to your data will make everyone smarter.

SAP EIM Overview

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Talend is an open source integration software provider specializing in data integration, master data management, data quality, big data integration, and enterprise application integration. It offers a platform and tools like Talend Data Integration and Talend Data Quality that help with Extract, Transfer, and Load (ETL) processes, ensuring data quality, and enabling integration across various data sources and targets. The presentation concluded with a live demo of Talend's enterprise service bus functionality for intelligent routing, mediation, and service enablement using open standards.

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AgileAnalytics: Agile Real-Time BI with Oracle Business Intelligence, Oracle ...

A successful real-time BI implementation involves integrating the logical and physical model, source and target databases, ETL subsystems, and front-end dashboards and reports. Agile methodologies often struggle to deliver real-time implementations due to the complexity of the intermingled moving parts. Using the Oracle Information Management Reference Architecture as a backdrop, attendees will see how to construct a complete real-time BI system using Oracle Business Intelligence, Oracle Data Integrator and Oracle GoldenGate, driven by an Agile approach focusing on user stories and time-boxed iterations.

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